Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A communication system comprising: an automatic speech recognizer configured to receive a speech signal of a speaker in a first language and to convert said speech signal into a text sequence in the first language; a speech analyzer configured to receive said speech signal, said speech analyzer configured to extract all paralinguistic characteristics of the speech signal in the first language from said speech signal; a translator coupled with said automatic speech recognizer, said translator configured to convert said text sequence from the first language to a second language; and a speech output device coupled with said automatic speech recognizer and said speech analyzer, said speech output device comprising a look-up table of paralinguistic characteristics mapping between the paralinguistic characteristics of the speech signal in the first language to paralinguistic characteristics of the speech signal in a second language, and said speech output device configured to transform all of the paralinguistic characteristics of the speech signal in the first language to the paralinguistic characteristics of the speech signal in the second language based on the mapping between the paralinguistic characteristics of the speech signal in the first language to the paralinguistic characteristics of the speech signal in the second language of the look-up table of paralinguistic characteristics and convert said translated text sequence in the second language into an output speech signal in the second language based on said paralinguistic characteristics of the speech signal in the second language, wherein the transformation of all the paralinguistic characteristics of the speech signal in the first language to the paralinguistic characteristics of the speech signal in the second language comprises transforming at least one paralinguistic characteristic of the speech signal in the first language imparting a connotation in the first language to a first word in the speech signal in the first language to at least one corresponding paralinguistic characteristic of the speech signal in the second language imparting the connotation in the second language to a second word of the speech signal in the second language, the second word in the second language being a translation of the first word in the first language, wherein said paralinguistic characteristics of the speech signal in the first language comprises at least one of a first pitch of the speech signal in the first language, a first amplitude of the speech signal in the first language, and a first rate of speech of the speech signal in the first language, and wherein said paralinguistic characteristics of the speech signal in the second language comprises at least one of a second pitch of the speech signal in the second language, a second amplitude of the speech signal in the second language, and a second rate of speech of the speech signal in the second language.
This communication system enables natural-sounding speech translation by preserving paralinguistic characteristics such as pitch, amplitude, and speech rate across languages. The system processes a speech signal in a first language through an automatic speech recognizer, converting it into a text sequence. Simultaneously, a speech analyzer extracts paralinguistic features from the original speech signal. A translator then converts the text into a second language. The speech output device uses a look-up table to map the original paralinguistic characteristics to corresponding characteristics in the second language, ensuring that connotations and emotional nuances are retained. For example, if a word in the first language is spoken with a specific pitch or amplitude to convey sarcasm or emphasis, the system applies equivalent paralinguistic features to its translation in the second language. This approach ensures that the translated speech maintains the original speaker's tone, emotion, and intent, improving the naturalness and effectiveness of cross-language communication. The system is particularly useful in applications requiring high-fidelity speech translation, such as real-time interpretation or multimedia localization.
2. The communication system of claim 1 , wherein said speech output device includes a personifier.
A communication system is designed to enhance interactions between users and automated systems by improving the naturalness and personalization of speech output. The system addresses the problem of robotic or impersonal speech in automated communication, which can reduce user engagement and satisfaction. The system includes a speech output device that generates spoken responses to user inputs, such as voice commands or text queries. To make these responses more relatable, the speech output device incorporates a personifier, which modifies the speech output to mimic human-like characteristics. This may include adjusting tone, pitch, pacing, or adding subtle variations in speech patterns to create a more natural and personalized interaction. The personifier can also adapt the speech output based on user preferences, historical interactions, or contextual factors, ensuring the communication feels tailored to the individual user. By integrating this personifier, the system aims to improve user experience by making automated interactions feel more human-like and engaging.
3. The communication system of claim 1 , wherein said automatic speech recognizer converts said speech signal into said text sequence based on a first algorithm.
A communication system is designed to process speech signals by converting them into text sequences using automatic speech recognition (ASR) technology. The system addresses the challenge of accurately transcribing spoken language into written form, which is critical for applications such as voice assistants, transcription services, and real-time captioning. The ASR component employs a first algorithm to perform this conversion, ensuring that the speech signal is accurately transformed into a text sequence. This algorithm may involve techniques such as acoustic modeling, language modeling, and decoding to interpret the speech signal and generate the corresponding text. The system may also include additional features, such as noise reduction or speaker diarization, to enhance the accuracy and reliability of the transcription process. By leveraging advanced speech recognition algorithms, the system aims to provide high-fidelity text output from spoken input, improving accessibility and efficiency in communication.
4. The communication system of claim 3 , further comprising a second automatic speech recognizer, said second automatic speech recognizer configured to convert said speech signal to a second text sequence based on a second algorithm.
This invention relates to a communication system designed to enhance speech recognition accuracy by utilizing multiple automatic speech recognition (ASR) algorithms. The system addresses the challenge of accurately transcribing speech in varying acoustic conditions or dialects by employing at least two distinct ASR algorithms. The first ASR algorithm processes a speech signal to generate a first text sequence. A second ASR algorithm, operating independently, converts the same speech signal into a second text sequence. The system may further include a fusion module that combines the outputs of the two ASR algorithms to produce a more accurate final transcription. This approach leverages the strengths of different recognition techniques, improving robustness in noisy environments or when dealing with diverse speech patterns. The system may also incorporate a confidence scoring mechanism to evaluate the reliability of each ASR output before fusion. By integrating multiple recognition pathways, the invention aims to overcome limitations of single-algorithm systems, particularly in applications requiring high accuracy, such as real-time transcription services, voice assistants, or accessibility tools. The use of parallel ASR processing allows for redundancy and cross-verification, enhancing overall performance.
5. The communication system of claim 4 , further comprising a text sequence comparator configured to compare said text sequence with said second text sequence.
A communication system is designed to enhance message transmission by analyzing and processing text sequences. The system includes a text sequence analyzer that extracts a first text sequence from a message and a text sequence generator that creates a second text sequence based on the first text sequence. The second text sequence may be a modified or encoded version of the first text sequence, ensuring secure or efficient transmission. Additionally, the system includes a text sequence comparator that compares the first text sequence with the second text sequence to verify accuracy, detect errors, or ensure consistency between the original and processed text. This comparison step helps maintain data integrity during transmission, particularly in applications where message accuracy is critical, such as secure communications, error detection, or data validation. The system may be used in various communication protocols or applications where text-based messages require processing, transformation, or verification before transmission or storage.
6. The communication system of claim 5 , wherein said text sequence comparator generates an error corrected text sequence based on the comparison of said text sequence and said second text sequence.
A communication system is designed to improve text transmission accuracy by comparing received text sequences with reference text sequences to detect and correct errors. The system includes a text sequence comparator that analyzes a received text sequence against a second text sequence, which may be a pre-stored reference or a previously transmitted version. The comparator identifies discrepancies between the two sequences and generates an error-corrected text sequence based on the comparison. This correction process ensures that any errors introduced during transmission or storage are detected and resolved, enhancing the reliability of text-based communication. The system may also include a text sequence receiver to obtain the initial text sequence and a text sequence storage unit to retain the second text sequence for comparison. The error correction mechanism may involve techniques such as pattern matching, checksum validation, or other error-detection algorithms to refine the received text sequence. This approach is particularly useful in applications where text integrity is critical, such as in messaging systems, data transmission protocols, or digital storage systems. The system ensures that the final output is a corrected version of the original text, minimizing errors and improving communication accuracy.
7. The communication system of claim 1 , wherein said translator includes a plurality of translators.
The communication system involves a translator that facilitates communication between devices using different protocols. The system addresses the challenge of interoperability in heterogeneous networks where devices operate on incompatible communication standards, leading to inefficiencies and connectivity issues. The translator acts as an intermediary, converting messages or data between the protocols of the communicating devices to ensure seamless interaction. The translator includes multiple translators, each capable of handling different protocol conversions. This modular approach allows the system to support a wide range of protocols and adapt to varying communication requirements. Each translator within the system is designed to process and convert data between specific pairs of protocols, ensuring accurate and efficient communication. The use of multiple translators enhances flexibility, scalability, and reliability, as the system can dynamically assign or activate the appropriate translator based on the protocols involved in a given communication session. This ensures that devices with different communication standards can interact without manual configuration or additional hardware, improving overall network efficiency and reducing compatibility barriers.
8. The communication system of claim 1 , wherein said output device converts said text sequence into the output speech signal using a text-to-speech algorithm.
A communication system is designed to facilitate interaction between a user and a remote device, particularly in scenarios where the user may have limited mobility or dexterity. The system includes an input device that captures a user's input, such as a sequence of text or commands, and a processing unit that processes this input to generate a corresponding output. The output is then transmitted to an output device, which converts the processed input into an audible speech signal using a text-to-speech algorithm. This allows the user to interact with the remote device through spoken feedback, enhancing accessibility and usability. The system may also include additional components, such as a display for visual feedback or a microphone for voice input, depending on the specific implementation. The text-to-speech conversion ensures that the output is delivered in a clear and intelligible manner, making it suitable for applications in assistive technology, remote control systems, or other communication interfaces where spoken output is beneficial. The system is particularly useful in environments where traditional input methods may be impractical or inaccessible.
9. A communication system comprising: a memory; one or more processors; and one or more modules stored in memory and configured for execution by the one or more processors, the one or more modules comprising: a speech input module configured to receive a speech signal of a speaker in a first language; an automatic speech recognizer module coupled with said speech input module, said automatic speech recognizer module configured to convert said speech signal into a text sequence in the first language; a speech analyzer module coupled with said speech input module, said speech analyzer module configured to extract all paralinguistic characteristics of the speech signal in the first language from said speech signal; a translator module coupled with said automatic speech recognizer module, said speech recognizer module configured to translate said text sequence from the first language to a second language; and an output speech module coupled with said translator module, said output speech module comprising a look-up table of paralinguistic characteristics mapping between the paralinguistic characteristics of the speech signal in the first language to paralinguistic characteristics of the speech signal in a second language, and said output speech module configured to transform all of the paralinguistic characteristics of the speech signal in the first language to the paralinguistic characteristics of the speech signal in the second language based on the mapping between the paralinguistic characteristics of the speech signal in the first language to the paralinguistic characteristics of the speech signal in the second language of the look-up table of paralinguistic characteristics and convert said translated text sequence in the second language into an output speech signal in the second language based on said paralinguistic characteristics of the speech signal in the second language, wherein the transformation of all the paralinguistic characteristics of the speech signal in the first language to the paralinguistic characteristics of the speech signal in the second language comprises transforming at least one paralinguistic characteristic of the speech signal in the first language imparting a connotation in the first language to a first word in the speech signal in the first language to at least one corresponding paralinguistic characteristic of the speech signal in the second language imparting the connotation in the second language to a second word of the speech signal in the second language, the second word in the second language being a translation of the first word in the first language, wherein said paralinguistic characteristics of the speech signal in the first language comprises at least one of a first pitch of the speech signal in the first language, a first amplitude of the speech signal in the first language, and a first rate of speech of the speech signal in the first language, and wherein said paralinguistic characteristics of the speech signal in the second language comprises at least one of a second pitch of the speech signal in the second language, a second amplitude of the speech signal in the second language, and a second rate of speech of the speech signal in the second language.
This communication system translates spoken language while preserving paralinguistic characteristics such as pitch, amplitude, and speech rate. The system receives a speech signal in a first language, converts it into text using automatic speech recognition, and extracts paralinguistic features from the original speech. The text is then translated into a second language. A look-up table maps paralinguistic characteristics from the first language to the second language, ensuring that connotations and emotional nuances are maintained. For example, if a word in the first language is spoken with a specific pitch or tone, the corresponding translated word in the second language will adopt a similar pitch or tone to convey the same meaning. The system then generates an output speech signal in the second language, incorporating the transformed paralinguistic features. This approach ensures that the translated speech retains the original speaker's emotional tone, emphasis, and other non-verbal cues, improving naturalness and comprehension in cross-language communication. The system is designed to handle multiple paralinguistic dimensions, including pitch, amplitude, and speech rate, to provide a more accurate and expressive translation.
10. The communication system of claim 9 , wherein said speech output module includes a personifier.
A communication system is designed to enhance user interaction by generating natural and personalized speech outputs. The system includes a speech output module that converts text or digital data into spoken language. This module incorporates a personifier, which modifies the speech output to mimic the voice, tone, or speaking style of a specific individual or character. The personifier may adjust pitch, pace, intonation, or other vocal characteristics to create a more engaging and lifelike interaction. The system may also include a text-to-speech (TTS) engine that processes input text and generates corresponding audio signals, which are then personalized by the personifier. Additionally, the system may feature a user interface for selecting or customizing the voice profile used by the personifier. This technology is particularly useful in applications such as virtual assistants, customer service automation, and interactive entertainment, where personalized speech enhances user experience and engagement. The personifier ensures that the speech output is not only intelligible but also tailored to the preferences or requirements of the user, improving the overall effectiveness of the communication system.
11. The communication system of claim 9 , wherein said automatic speech recognizer module converts said speech signal into said text sequence based on a first algorithm.
The communication system involves a speech recognition and text processing system designed to improve the accuracy and efficiency of converting spoken language into written text. The system addresses challenges in automatic speech recognition (ASR), particularly in accurately transcribing speech signals into text sequences, especially in noisy environments or with varying accents. A key component is an automatic speech recognizer module that processes speech signals using a first algorithm to generate a text sequence. This module may employ machine learning models, statistical methods, or hybrid approaches to enhance recognition accuracy. The system may also include additional modules for refining the text output, such as error correction, context-aware processing, or user-specific adaptation. The overall goal is to provide a robust and adaptable speech-to-text solution for applications like voice assistants, transcription services, or real-time communication systems. The system may further integrate with other components, such as natural language processing (NLP) engines or user interface elements, to deliver a seamless and accurate text representation of spoken input. The use of a first algorithm in the speech recognizer ensures that the system can be optimized for specific use cases, such as handling different languages, dialects, or environmental conditions.
12. The communication system of claim 11 , further comprising a second automatic speech recognizer module, said second automatic speech recognizer module configured to convert said speech signal to a second text sequence based on a second algorithm.
This invention relates to a communication system designed to enhance speech recognition accuracy by utilizing multiple speech recognition algorithms. The system addresses the problem of errors in automatic speech recognition (ASR) caused by variations in speech patterns, accents, or background noise, which can lead to misinterpretations of spoken input. The system includes a primary automatic speech recognizer module that converts a speech signal into a first text sequence using a first recognition algorithm. To improve reliability, the system further includes a second automatic speech recognizer module that processes the same speech signal using a different, second algorithm to generate a second text sequence. By comparing or combining the outputs from both modules, the system can achieve more accurate transcription or command interpretation. The dual-module approach allows the system to leverage the strengths of different recognition algorithms, reducing the likelihood of errors from any single method. This is particularly useful in applications requiring high accuracy, such as voice-controlled devices, transcription services, or real-time communication systems. The system may also include additional components to process or analyze the text sequences, such as natural language processing modules or user interface elements. The invention aims to provide a robust solution for converting speech to text with improved precision and adaptability.
13. The communication system of claim 12 , further comprising a text sequence comparator module configured to compare said text sequence with said second text sequence.
This invention relates to a communication system designed to enhance message transmission and processing. The system addresses the challenge of accurately identifying and handling text sequences within communications, particularly in scenarios where text data needs to be compared or validated against a reference. The system includes a text sequence comparator module that compares a received text sequence with a second text sequence, which may be a predefined or previously stored sequence. This comparison can be used for tasks such as message verification, error detection, or content matching. The system may also include a message processor that extracts text sequences from incoming messages and a storage module that retains the second text sequence for comparison purposes. The comparator module evaluates the similarity or differences between the sequences, enabling the system to determine whether the received text matches, partially matches, or differs from the reference sequence. This functionality is useful in applications like spam filtering, authentication, or data consistency checks, where accurate text sequence analysis is critical. The system ensures reliable communication by validating text content against known patterns or expected values.
14. The communication system of claim 13 , wherein said text sequence comparator module generates an error corrected text sequence based on the comparison of said text sequence and said second text sequence.
This invention relates to communication systems designed to improve text transmission accuracy. The system addresses the problem of errors in text data during transmission, which can occur due to noise, interference, or other disruptions in communication channels. The system includes a text sequence comparator module that compares a transmitted text sequence with a second text sequence, which may be a reference or previously received version. The comparator module generates an error-corrected text sequence based on this comparison, ensuring that the final output is accurate and free from transmission-induced errors. The system may also include a text sequence generator module that produces the initial text sequence for transmission, and a text sequence receiver module that captures the transmitted text sequence. The comparator module processes the received text sequence against the second text sequence, applying error correction techniques to produce a corrected version. This ensures reliable text communication in environments where errors are likely, such as wireless or noisy networks. The invention enhances data integrity by dynamically correcting errors during transmission, improving the overall reliability of text-based communication systems.
15. The communication system of claim 9 , wherein said translator module comprises a plurality of translator modules.
A communication system is designed to facilitate data exchange between devices operating on different communication protocols. The system addresses the challenge of interoperability in heterogeneous networks where devices use incompatible protocols, leading to communication failures or inefficiencies. The system includes a translator module that converts data between different protocols, ensuring seamless communication. The translator module is configured to handle multiple protocol conversions, allowing devices to communicate regardless of their native protocols. The system may also include a protocol analyzer to identify the protocols used by connected devices and a routing module to direct data through the appropriate translator module. The translator module can be implemented as a plurality of translator modules, each specialized for specific protocol conversions, improving efficiency and scalability. This modular approach allows the system to adapt to new protocols by adding or updating individual translator modules without overhauling the entire system. The system ensures reliable data transmission across diverse networks, enhancing interoperability and reducing the need for manual protocol conversion.
16. The communication system of claim 9 , wherein said output speech module converts said translated text sequence into an output speech signal using a text-to-speech algorithm.
This invention relates to a communication system designed to facilitate real-time language translation between speakers of different languages. The system addresses the challenge of enabling seamless, bidirectional communication where participants speak different languages without requiring manual intervention or delays. The system includes an input speech module that captures and processes spoken input from a first speaker, converting it into a text sequence. This text is then translated into a target language using a machine translation module. The translated text is subsequently converted back into an output speech signal by an output speech module, which employs a text-to-speech algorithm to generate natural-sounding speech in the target language. The system may also include a display module to present the translated text visually, ensuring clarity and accessibility. Additionally, the system may incorporate a feedback mechanism to refine translations based on user corrections, improving accuracy over time. The communication system is particularly useful in scenarios such as international business meetings, customer service interactions, or multilingual conferences, where real-time translation is essential for effective communication.
17. A speech morphing communication system comprising: a speech input device configured to receive a speech signal of a speaker in a first language; a first automatic speech recognizer and a second automatic speech recognizer coupled with said input device, said first automatic speech recognizer configured to convert said speech signal into a first text sequence in the first language and said second automatic speech recognizer configured to convert said speech signal into a second text sequence in the first language; a text sequence comparator coupled with said first automatic speech recognizer and said second automatic speech recognizer, said text sequence comparator configured to select one text sequence from among said first text sequence and said second text sequence; a speech analyzer coupled with said speech input device, said speech analyzer configured to extract all paralinguistic characteristics of the speech signal in the first language from said speech signal; one or more translators coupled with said text analyzer, said one or more translators configured to translate said selected text sequence from the first language to one or more second languages to generate a translated text sequence in the one or more second languages; and a speech output device comprising a look-up table of paralinguistic characteristics mapping between the paralinguistic characteristics of the speech signal in the first language to paralinguistic characteristics of the speech signal in the one or more second languages, and said speech output device configured to transform all of the paralinguistic characteristics of the speech signal in the first language to the paralinguistic characteristics of the speech signal in the one or more second languages based on the mapping between the paralinguistic characteristics of the speech signal in the first language to the paralinguistic characteristics of the speech signal in the one or more second languages of the look-up table of paralinguistic characteristics and convert said translated text sequence into an output speech signal in the one or more second languages based on said paralinguistic characteristics of the speech signal in the one or more second languages, wherein the transformation of all the paralinguistic characteristics of the speech signal in the first language to the paralinguistic characteristics of the speech signal in the one or more second languages comprises transforming at least one paralinguistic characteristic of the speech signal in the first language imparting a connotation in the first language to a first word in the speech signal in the first language to at least one corresponding paralinguistic characteristic of the speech signal in the one or more second languages imparting the connotation in the one or more second languages to a second word of the speech signal in the one or more second languages, the second word in the one or more second languages being a translation of the first word in the first language, wherein said paralinguistic characteristics of the speech signal in the first language comprises at least one of a first pitch of the speech signal in the first language, a first amplitude of the speech signal in the first language, and a first rate of speech of the speech signal in the first language, and wherein said paralinguistic characteristics of the speech signal in the one or more second languages comprises at least one of a second pitch of the speech signal in the one or more second languages, a second amplitude of the speech signal in the one or more second languages, and a second rate of speech of the speech signal in the one or more second languages.
A speech morphing communication system translates spoken language while preserving paralinguistic characteristics such as pitch, amplitude, and speech rate. The system receives a speech signal in a first language and processes it through two automatic speech recognizers to generate two text sequences in the first language. A comparator selects the most accurate text sequence. A speech analyzer extracts paralinguistic features from the original speech signal. The selected text is then translated into one or more target languages. A speech output device uses a look-up table to map paralinguistic characteristics from the first language to the target languages, ensuring that connotations and emotional nuances are preserved. For example, the pitch, amplitude, or speech rate of a word in the original language is transformed to convey the same connotation in the translated word. The system converts the translated text into speech in the target language while maintaining the original paralinguistic features, ensuring natural and contextually appropriate delivery. This approach enhances cross-language communication by retaining the speaker's emotional and expressive qualities in the translated output.
18. A method for converting speech into text comprising: receiving an input speech signal of a speaker in a first language; extracting all paralinguistic characteristics of the speech signal in the first language from said input speech signal; converting said input speech signal to one or more text sequences in the first language; transforming all of the paralinguistic characteristics of the speech signal in the first language to paralinguistic characteristics of the speech signal in a second language; translating said text sequence from the first language to the second language; and transforming said text sequence into an output speech signal in the second language based on said paralinguistic characteristics of the speech signal in the second language, wherein the transforming of the paralinguistic characteristics comprises: reading from a look-up table of paralinguistic characteristics mapping between the paralinguistic characteristics of the speech signal in the first language to paralinguistic characteristics of the speech signal in a second language; and transforming at least one paralinguistic characteristic of the speech signal in the first language imparting a connotation in the first language to a first word in the speech signal in the first language to at least one corresponding paralinguistic characteristic of the speech signal in the second language imparting the connotation in the second language to a second word of the speech signal in the second language based on the mapping between the paralinguistic characteristics of the speech signal in the first language to the paralinguistic characteristics of the speech signal in the second language of the look-up table of paralinguistic characteristics, the second word in the second language being a translation of the first word in the first language, wherein said paralinguistic characteristics of the speech signal in the first language comprises at least one of a first pitch of the speech signal in the first language, a first amplitude of the speech signal in the first language, and a first rate of speech of the speech signal in the first language, and wherein said paralinguistic characteristics of the speech signal in the second language comprises at least one of a second pitch of the speech signal in the second language, a second amplitude of the speech signal in the second language, and a second rate of speech of the speech signal in the second language.
This invention relates to speech-to-text conversion with cross-lingual paralinguistic preservation. The problem addressed is the loss of emotional or contextual nuances (paralinguistic characteristics) when translating speech from one language to another. The method processes an input speech signal in a first language by first extracting paralinguistic features such as pitch, amplitude, and speech rate. The speech is then converted to text in the first language, which is subsequently translated into a second language. The extracted paralinguistic characteristics are transformed into corresponding characteristics in the second language using a predefined look-up table that maps these features between languages. The translated text is then synthesized into speech in the second language, incorporating the transformed paralinguistic traits to preserve the original connotations. For example, if a word in the first language is spoken with a high pitch to convey excitement, the corresponding translated word in the second language will also be synthesized with a high pitch to maintain the same emotional tone. This approach ensures that the translated speech retains the original speaker's intended emotional and contextual nuances.
19. The method of claim 18 , wherein said converting said input speech signal includes generating a plurality of text sequences and determining a score for each one of said plurality of text sequences.
This invention relates to speech recognition systems, specifically improving the accuracy of converting spoken language into text. The problem addressed is the inherent ambiguity in speech signals, where multiple possible text sequences may correspond to a single input. The invention provides a method to enhance speech-to-text conversion by generating multiple candidate text sequences from an input speech signal and evaluating each candidate using a scoring mechanism. The scoring process assesses the likelihood of each text sequence being the correct transcription, improving the system's ability to select the most accurate output. The method may involve statistical models, machine learning techniques, or other computational approaches to assign scores to the candidate sequences. By analyzing multiple possible interpretations of the speech input, the system reduces errors and improves the reliability of the final transcribed text. This approach is particularly useful in applications requiring high accuracy, such as voice assistants, transcription services, and real-time communication systems. The invention may also integrate with other speech processing techniques, such as noise reduction or speaker identification, to further refine the transcription process.
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August 18, 2020
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